As hospitals across the country expedite investments in automation, such as automated endoscope reprocessors (AERs), surgical instrument tracking platforms, and preliminary AI systems employed for enhancing workflow efficiency, the role of human competence remains pivotal in the domain of infection prevention. Although these automation tools hold immense potential for consistency, improved efficiency, and minimized variability, they cannot override the impeccable competency, judgement, and scrupulousness that healthcare professionals exhibit. In fact, automation has been pictured as presenting new challenges and cognitive demands that only a skilfully trained workforce can successfully navigate.
Consequently, an ignorance towards human factors such as their interaction with tools, systems, and each other, could keep the fruits of automation unreachable. Notwithstanding the advent of artificial intelligence, a machine has yet to compete with the human ability to understand, adapt and problem solve. Several recent patient safety studies have found that automated systems can’t eliminate errors unless humans are trained effectively, adding a new layer to this intricate relationship between man and machine.
A recent study exploring assembly errors in sterile processing across globally recognized health systems found errors were attributed to system and human issues, not technological glitches. In hospitals using automated endoscope reprocessors, the human touch continues to be critical in preventing infection. When the manual cleaning aspect of reprocessing was inadequate, even a sophisticated AER couldn’t eliminate risk.
The crux is, automation is a supportive partner to human vigilance, not a replacement. As the infection prevention arena continues to layer in more sophisticated technologies, the work process does not simplify, rather it becomes more interdependent. Hence, system reliability is found to depend less on individual tools and more on cross-department coordination, effective communication, and clearly defined roles.
Finally, the role of competent human action is highlighted in artificial intelligence tools for infection prevention and workflow optimization. These tools, for example, may flag anomalies or predict high-risk scenarios using historical data, but the risk of bias entering these AI systems is ever-present, notably manifesting in interpretation of data.
The collaborative performance between technology and competent human action thus promises improvement in safety and efficiency in the realm of infection prevention. In essence, a competent infection preventionist working with sophisticated technologies like AERs and AI can make the best use of automation while mitigating its risks. This powerful synergy is the future of sterile processing, with an emphasis on human competencies, surveillance and a well-evaluated system design.